Tissue microarray technology continues to evolve in the cancer genomic era, and has a central role in validating the expression of proteins associated with emerging genetic mutation phenotypes and transcriptional profiling studies. Primary uses of TMAs have always been for immunohistochemistry validation of differentially expressed proteins in a particular cancer type, particularly as applied to biomarker, diagnostic, prognostic, prevention and therapeutic research purposes. Direct analysis of TMAs for DNA or RNA profiling and proteomic analyses are also major research uses. The main advantages of experiments performed with TMAs are the availability of histopathology and clinically relevant tissue sections from multiple individual samples, providing elements of throughput, statistical relevance and multiplexed analysis of diverse molecular targets. The goal of this application is to extend use of TMAs as a tool for the study of glycosylation in cancer development and progression. It is well documented that malignant transformation and cancer progression result in fundamental changes in the glycosylation patterns of cell surface and secreted glycoproteins. It is currently difficult to assess these glycosylation changes in tissues in a global manner, as only a few carbohydrate antigen antibodies specific to one glycoform or broad affinity lectins are available. To address this, our lab has recently developed a novel method to profile N-linked glycans directly on tissue using MALDI-imaging mass spectrometry. Depending on the tissue, currently 30-40 N-glycan species can be simultaneously detected by this method, linked directly with their histopathology expression and tissue distribution. This approach has been adapted to formalin-fixed tissues, and in combination with a custom TMA and high-resolution MALDI-FTICR mass spectrometer, a method to profile multiple N-glycans in a TMA format will be optimized for multiple tissue types. We anticipate optimizing the approach for applicability to any TMA, and to accomplish this, three Specific Aims are proposed: Aim 1. Optimize MALDI imaging mass spectrometry analysis of N-linked glycans using a mixed TMA of 8 cancer tissue types. Aim 2. Increase the total number of detected glycans and improve detection of higher mass glycans using on-slide chemical derivatization. Aim 3. Confirm glycan structures, categorize their detection per cancer tissue and define analytical detection parameters of the assay. Our approach will be transformative in that all detectable glycan changes associated with a given cancer type can be profiled simultaneously in a TMA format. As guided by a pathologist, the potential impact of the approach is its use with any TMA cancer type for prevention, progression, prognosis, and biomarker studies.